The Influence of Solid Earth Deformations on Semidiurnal and Diurnal Oceanic Tides

Author(s):  
W. Zahel
2009 ◽  
Vol 5 (H15) ◽  
pp. 215-215 ◽  
Author(s):  
Sigrid Englich ◽  
Harald Schuh ◽  
Robert Weber

AbstractThe Earth rotation rate and consequently universal time (UT1) and length of day (LOD) are periodically affected by solid Earth tides and oceanic tides. Solid Earth tides induce changes with periods from around 5 days to 18.6 years, with the largest amplitudes occurring at fortnightly, monthly, semi-annual and annual periods, and at 18.6 years. The principal variations caused by oceanic tides have diurnal and semi-diurnal periods. For the investigation of the tidal effects with periods of up to 35 days, UT1 series are estimated from VLBI observation data of the time interval 1984–2008. The amplitudes and phases of the terms of interest are calculated and the results for diurnal and sub-diurnal periods are compared and evaluated with tidal variations derived from a GNSS-based LOD time series of 8 months. The observed tidal signals are finally compared to the predicted tidal variations according to recent geophysical models.


2020 ◽  
Vol 31 (S1) ◽  
pp. 15-25 ◽  
Author(s):  
Roger Haagmans ◽  
Christian Siemes ◽  
Luca Massotti ◽  
Olivier Carraz ◽  
Pierluigi Silvestrin

Abstract The paper addresses the preparatory studies of future ESA mission concepts devoted to improve our understanding of the Earth’s mass change phenomena causing temporal variations in the gravity field, at different temporal and spatial scales, due to ice mass changes of ice sheets and glaciers, continental water cycles, ocean masses dynamics and solid Earth deformations. The ESA initiatives started in 2003 with a study on observation techniques for solid Earth missions and continued through several studies focusing on the satellite system, technology development for propulsion and distance metrology, preferred mission concepts, the attitude and orbit control system, as well as the optimization of the satellite constellation. These activities received precious inputs from the GOCE, GRACE and GRACE-FO missions. More recently, several studies related to new sensor concepts based on cold atom interferometry (CAI) were conducted, mainly focusing on technology development for different instrument configurations (GOCE-like and GRACE-like) and including validation activities, e.g. a first successful airborne survey with a CAI gravimeter. The latest results concerning the preferred satellite architectures and constellations, payload design and estimated science performance will be presented as well as remaining open issues for future concepts.


2018 ◽  
Author(s):  
E. Bruce Watson ◽  
◽  
Daniele J. Cherniak ◽  
Maxwell S. Drexler ◽  
Morgan F. Schaller ◽  
...  

Eos ◽  
1994 ◽  
Vol 75 (6) ◽  
pp. 59
Author(s):  
Deborah Gray

2020 ◽  
Vol 1 (1-2) ◽  
pp. 28-35 ◽  
Author(s):  
Masaki Yoshida ◽  
M. Santosh
Keyword(s):  

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1403
Author(s):  
Xin Jin ◽  
Xin Liu ◽  
Jinyun Guo ◽  
Yi Shen

Geocenter is the center of the mass of the Earth system including the solid Earth, ocean, and atmosphere. The time-varying characteristics of geocenter motion (GCM) reflect the redistribution of the Earth’s mass and the interaction between solid Earth and mass loading. Multi-channel singular spectrum analysis (MSSA) was introduced to analyze the GCM products determined from satellite laser ranging data released by the Center for Space Research through January 1993 to February 2017 for extracting the periods and the long-term trend of GCM. The results show that the GCM has obvious seasonal characteristics of the annual, semiannual, quasi-0.6-year, and quasi-1.5-year in the X, Y, and Z directions, the annual characteristics make great domination, and its amplitudes are 1.7, 2.8, and 4.4 mm, respectively. It also shows long-period terms of 6.09 years as well as the non-linear trends of 0.05, 0.04, and –0.10 mm/yr in the three directions, respectively. To obtain real-time GCM parameters, the MSSA method combining a linear model (LM) and autoregressive moving average model (ARMA) was applied to predict GCM for 2 years into the future. The precision of predictions made using the proposed model was evaluated by the root mean squared error (RMSE). The results show that the proposed method can effectively predict GCM parameters, and the prediction precision in the three directions is 1.53, 1.08, and 3.46 mm, respectively.


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